K
K. P. Soman
Researcher at Amrita Vishwa Vidyapeetham
Publications - 504
Citations - 8779
K. P. Soman is an academic researcher from Amrita Vishwa Vidyapeetham. The author has contributed to research in topics: Deep learning & Support vector machine. The author has an hindex of 32, co-authored 489 publications receiving 5773 citations. Previous affiliations of K. P. Soman include Indian Institute of Technology Kharagpur & Indian Institutes of Technology.
Papers
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Journal ArticleDOI
Deep Learning Approach for Intelligent Intrusion Detection System
R. Vinayakumar,Mamoun Alazab,K. P. Soman,Prabaharan Poornachandran,Ameer Al-Nemrat,Sitalakshmi Venkatraman +5 more
TL;DR: A highly scalable and hybrid DNNs framework called scale-hybrid-IDS-AlertNet is proposed which can be used in real-time to effectively monitor the network traffic and host-level events to proactively alert possible cyberattacks.
Proceedings ArticleDOI
Stock price prediction using LSTM, RNN and CNN-sliding window model
TL;DR: This work uses three different deep learning architectures for the price prediction of NSE listed companies and compares their performance and applies a sliding window approach for predicting future values on a short term basis.
Proceedings ArticleDOI
Applying convolutional neural network for network intrusion detection
TL;DR: This paper models network traffic as time-series, particularly transmission control protocol / internet protocol (TCP/IP) packets in a predefined time range with supervised learning methods such as multi-layer perceptron (MLP), CNN, CNN-recurrent neural network (CNN-RNN), CNN-long short-term memory ( CNN-LSTM) and CNN-gated recurrent unit (GRU), using millions of known good and bad network connections.
Journal ArticleDOI
A novel method for detecting R-peaks in electrocardiogram (ECG) signal
TL;DR: This paper demonstrates that the proposed preprocessor with a Shannon energy envelope (SEE) estimator is better able to detect R-peaks than other well-known methods in case of noisy or pathological signals.
Journal ArticleDOI
NSE Stock Market Prediction Using Deep-Learning Models
TL;DR: Four types of deep learning architectures are used i.e Multilayer Perceptron (MLP), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) for predicting the stock price of a company based on the historical prices available for day-wise closing price of two different stock markets.